Download Udemy - Artificial Intelligence Reinforcement Learning in Python torrent

Udemy - Artificial Intelligence Reinforcement Learning in Python

Torrent:	Udemy - Artificial Intelligence Reinforcement Learning in Python
Description:	Udemy - Artificial Intelligence Reinforcement Learning in Python The complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning. Created by Lazy Programmer Inc. Last updated 1/2019 For more Udemy Courses: https://freecoursesite.com
Downloads:	76
Category:	Other /Tutorials
Size:	1.2 GB
Show Files »	[FreeCourseSite.com] Udemy - Artificial Intelligence Reinforcement Learning in Python 1. Introduction and Outline 1. Introduction and outline.mp4 (10.1 MB) 1. Introduction and outline.vtt (12.0 KB) 2. What is Reinforcement Learning.mp4 (22.0 MB) 2. What is Reinforcement Learning.vtt (24.0 KB) 3. Where to get the Code.mp4 (4.5 MB) 3. Where to get the Code.vtt (4.9 KB) 4. Strategy for Passing the Course.mp4 (9.5 MB) 4. Strategy for Passing the Course.vtt (10.7 KB) 2. Return of the Multi-Armed Bandit 1. Problem Setup and The Explore-Exploit Dilemma.mp4 (6.5 MB) 1. Problem Setup and The Explore-Exploit Dilemma.vtt (7.1 KB) 2. Epsilon-Greedy.mp4 (2.8 MB) 2. Epsilon-Greedy.vtt (2.9 KB) 3. Updating a Sample Mean.mp4 (2.2 MB) 3. Updating a Sample Mean.vtt (2.0 KB) 4. Comparing Different Epsilons.mp4 (8.0 MB) 4. Comparing Different Epsilons.vtt (4.9 KB) 5. Optimistic Initial Values.mp4 (5.1 MB) 5. Optimistic Initial Values.vtt (3.0 KB) 6. UCB1.mp4 (8.2 MB) 6. UCB1.vtt (7.4 KB) 7. Bayesian Thompson Sampling.mp4 (51.8 MB) 7. Bayesian Thompson Sampling.vtt (11.0 KB) 8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 (10.6 MB) 8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.vtt (5.5 KB) 9. Nonstationary Bandits.mp4 (7.5 MB) 9. Nonstationary Bandits.vtt (7.1 KB) 3. Build an Intelligent Tic-Tac-Toe Agent 1. Naive Solution to Tic-Tac-Toe.mp4 (6.1 MB) 1. Naive Solution to Tic-Tac-Toe.vtt (6.6 KB) 10. Tic Tac Toe Code Main Loop and Demo.mp4 (9.4 MB) 10. Tic Tac Toe Code Main Loop and Demo.vtt (8.4 KB) 11. Tic Tac Toe Summary.mp4 (8.3 MB) 11. Tic Tac Toe Summary.vtt (9.3 KB) 2. Components of a Reinforcement Learning System.mp4 (12.7 MB) 2. Components of a Reinforcement Learning System.vtt (13.4 KB) 3. Notes on Assigning Rewards.mp4 (4.2 MB) 3. Notes on Assigning Rewards.vtt (4.5 KB) 4. The Value Function and Your First Reinforcement Learning Algorithm.mp4 (103.7 MB) 4. The Value Function and Your First Reinforcement Learning Algorithm.vtt (21.7 KB) 5. Tic Tac Toe Code Outline.mp4 (5.0 MB) 5. Tic Tac Toe Code Outline.vtt (5.9 KB) 6. Tic Tac Toe Code Representing States.mp4 (4.4 MB) 6. Tic Tac Toe Code Representing States.vtt (4.5 KB) 7. Tic Tac Toe Code Enumerating States Recursively.mp4 (9.8 MB) 7. Tic Tac Toe Code Enumerating States Recursively.vtt (10.3 KB) 8. Tic Tac Toe Code The Environment.mp4 (10.0 MB) 8. Tic Tac Toe Code The Environment.vtt (10.9 KB) 9. Tic Tac Toe Code The Agent.mp4 (9.0 MB) 9. Tic Tac Toe Code The Agent.vtt (10.0 KB) 4. Markov Decision Proccesses 1. Gridworld.mp4 (3.4 MB) 1. Gridworld.vtt (3.7 KB) 2. The Markov Property.mp4 (7.2 MB) 2. The Markov Property.vtt (7.7 KB) 3. Defining and Formalizing the MDP.mp4 (6.6 MB) 3. Defining and Formalizing the MDP.vtt (7.2 KB) 4. Future Rewards.mp4 (5.2 MB) 4. Future Rewards.vtt (5.5 KB) 5. Value Function Introduction.mp4 (19.7 MB) 5. Value Function Introduction.vtt (14.5 KB) 6. Value Functions.mp4 (8.3 MB) 6. Value Functions.vtt (11.0 KB) 7. Bellman Examples.mp4 (87.1 MB) 7. Bellman Examples.vtt (25.8 KB) 8. Optimal Policy and Optimal Value Function.mp4 (3.2 MB) 8. Optimal Policy and Optimal Value Function.vtt (4.7 KB) 9. MDP Summary.mp4 (2.4 MB) 9. MDP Summary.vtt (2.4 KB) 5. Dynamic Programming 1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4 (4.8 MB) 1. Intro to Dynamic Programming and Iterative Policy Evaluation.vtt (4.9 KB) 10. Dynamic Programming Summary.mp4 (8.3 MB) 10. Dynamic Programming Summary.vtt (8.6 KB) 2. Gridworld in Code.mp4 (11.5 MB) 2. Gridworld in Code.vtt (10.0 KB) 3. Iterative Policy Evaluation in Code.mp4 (12.1 MB) 3. Iterative Policy Evaluation in Code.vtt (9.3 KB) 4. Policy Improvement.mp4 (4.5 MB) 4. Policy Improvement.vtt (4.7 KB) 5. Policy Iteration.mp4 (3.1 MB) 5. Policy Iteration.vtt (3.2 KB) 6. Policy Iteration in Code.mp4 (7.6 MB) 6. Policy Iteration in Code.vtt (5.6 KB) 7. Policy Iteration in Windy Gridworld.mp4 (9.1 MB) 7. Policy Iteration in Windy Gridworld.vtt (7.5 KB) 8. Value Iteration.mp4 (6.2 MB) 8. Value Iteration.vtt (6.4 KB) 9. Value Iteration in Code.mp4 (4.9 MB) 9. Value Iteration in Code.vtt (3.0 KB) 6. Monte Carlo 1. Monte Carlo Intro.mp4 (5.0 MB) 1. Monte Carlo Intro.vtt (5.4 KB) 2. Monte Carlo Policy Evaluation.mp4 (8.8 MB) 2. Monte Carlo Policy Evaluation.vtt (9.8 KB) 3. Monte Carlo Policy Evaluation in Code.mp4 (7.9 MB) 3. Monte Carlo Policy Evaluation in Code.vtt (5.6 KB) 4. Policy Evaluation in Windy Gridworld.mp4 (7.8 MB) 4. Policy Evaluation in Windy Gridworld.vtt (4.9 KB) 5. Monte Carlo Control.mp4 (9.3 MB) 5. Monte Carlo Control.vtt (9.3 KB) 6. Monte Carlo Control in Code.mp4 (10.2 MB) 6. Monte Carlo Control in Code.vtt (5.3 KB) 7. Monte Carlo Control without Exploring Starts.mp4 (4.6 MB) 7. Monte Carlo Control without Exploring Starts.vtt (5.0 KB) 8. Monte Carlo Control without Exploring Starts in Code.mp4 (8.1 MB) 8. Monte Carlo Control without Exploring Starts in Code.vtt (3.3 KB) 9. Monte Carlo Summary.mp4 (5.7 MB) 9. Monte Carlo Summary.vtt (6.5 KB) files
Added:	2019-01-09 13:07:18
Language:	English
Peers:	Seeders : 11 , Leechers : 9
Tags:	Udemy Artificial Intelligence Reinforcement Learning in Python
Release name:	Udemy - Artificial Intelligence Reinforcement Learning in Python
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